Agricultural Ethics & AI
Towards a Method to Reflect on Foundational Structures: The Case of Precision Farming
Mariska Thalitha Bosschaert
This paper introduces a novel 5-step method for reflecting on meta-physical structures within technological advancements like precision farming. By adapting Gilbert Simondon's evolutionary perspective, the method helps reveal how digitalization fundamentally alters our understanding and experience of the world, identifying shifts towards standardization and increased trust in digital outcomes. Applied to agriculture, it highlights potential implications such as the loss of embodied knowledge and meaning, advocating for early intervention in technology development.
Executive Impact Summary
This research provides a critical framework for enterprise leaders navigating the ethical and philosophical shifts introduced by AI in agriculture, ensuring sustainable and meaningful integration.
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Key Method Steps
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Foundational Shifts Identified
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Core Implications Explored
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on Meta-Physical Structures
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
The Simondon Method
Digitalization's Impact
Precision Farming Ethics
A New Lens for Meta-Physical Reflection
The core of this research is a novel 5-step method, building on Gilbert Simondon's philosophy of technical objects and their evolution. This approach moves beyond traditional sociological analyses to examine how technological shifts, particularly digitalization, redefine our fundamental understanding and experience of the world – what becomes 'self-evident'.
By focusing on discontinuities in technological evolution and the changing nature of the 'pre-individual' state before and after the emergence of 'epitome technologies,' the method offers a robust framework to identify and critically examine shifts in meta-physical structures without inherent normative biases.
Reshaping Reality: Standardization & Trust
Digitalization is not merely a technical upgrade; it's a profound meta-physical shift. The paper identifies two key 'epitome technologies' that drive this transformation: the electric telegraph (pioneering binary systems and standardization) and algorithms (fostering trust in digital judgment). These technologies, though distinct, have collectively pushed society towards a default mode of understanding and experiencing the world through standardization and reliance on digital outputs.
This process, while offering efficiency, often leads to a subtle but significant loss of meaning and a tendency to overlook alternative solutions or human abilities, as digital representations prioritize measurable data over nuanced, embodied experience.
Navigating the Meta-Physical Landscape of Modern Agriculture
Precision farming, as the digitalization of agriculture, inherits and accelerates these meta-physical shifts. The paper argues that as farmers increasingly rely on digital screens and algorithmic recommendations, their direct observational capabilities and embodied knowledge may erode. Concepts like "crops vs. weeds" become mediated through data, potentially losing their intuitive, self-evident distinction. This transition is not teleological but a complex interplay of human desires, technological possibilities, and milieus.
The crucial implication for precision farming is the risk of a fundamental change in the experience of farming, where digital output replaces sensory richness, leading to a profound loss of meaning in the practice and an uncritical trust in automated systems, even at the cost of alternative, perhaps more holistic, approaches.
Enterprise Process Flow: The 5-Step Reflection Method
Step 1: Identify the Epitome Technology
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Step 2: Identify the Pre-individual Before and After
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Step 3: Compare Pre-individuals & Reflect on Changes in Understanding
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Step 4: Identify Meta-Physical Structures in Practice
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Step 5: Reflect on Changes in Understanding in Practice
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Fundamental Meta-Physical Shifts Driven by Digitalization: Standardization & Trust in Algorithms.
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Case Study: The "Cyborg Farmer" & The Path Dependency Challenge
The paper highlights the concept of the "cyborg farmer" – an individual who combines digital insights with direct observation. While this hybrid approach offers a temporary solution, the underlying meta-physical shifts pose a significant challenge. As trust in digital systems grows, direct observation and embodied knowledge risk being seen as outdated.
This creates a path dependency: initial moves in one direction elicit further moves in the same direction, making reversal difficult once foundational structures have changed. For instance, some farmers already report diminished trust in direct field assessment. This underscores the urgency of proactive reflection on these meta-physical shifts to prevent an irreversible loss of meaning and alternative ways of farming.
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Your AI Transformation Roadmap
A phased approach to integrate advanced AI solutions, ensuring ethical considerations and foundational structures are addressed at every step.
Phase 1: Discovery & Foundational Assessment
Comprehensive analysis of current agricultural practices, identifying key areas for AI integration while assessing existing meta-physical structures and potential shifts.
Phase 2: Ethical Design & Solution Prototyping
Co-creating AI solutions that align with desired values, balancing efficiency with the preservation of meaning and embodied knowledge, using insights from the reflection method.
Phase 3: Pilot Implementation & Iteration
Deploying AI in controlled environments, meticulously monitoring impact on farmer experience and understanding, and iterating based on real-world feedback and meta-physical implications.
Phase 4: Full-Scale Integration & Continuous Reflection
Scaling AI solutions across operations, establishing mechanisms for ongoing ethical review, and fostering a culture of continuous reflection on how technology shapes our worldviews.
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